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Inter-Media Hashing for Large-scale Retrieval from Heterogeneous Data Sources

Summary: Proposes Inter-Media Hashing (IMH) for large-scale cross-modal retrieval across heterogeneous data sources. Maps multimodal data to a common Hamming space for fast search (XOR/bit-count) and learns hashing functions via linear regression for efficient online encoding. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4745
Venue
SIGMOD
Year
2013
Pagerank
6.9322681e-05
Overall Rank
4,060 | 72.15%
DOI
10.1145/2463676.2465274

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{song_sigmod13,
        title = {{Inter-Media Hashing for Large-scale Retrieval from Heterogeneous Data Sources}},
        author = {Song, Jingkuan and Yang, Yang and Yang, Yi and Huang, Zi and Shen, Heng Tao},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465274},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465274},
        year = {2013}
}

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